Currently, flight devices like Unmanned Aerial Vehicles (UAV), due to the convenience and security thereof, have been widely used in fields such as agricultural production, geological survey, meteorological monitoring, power line inspection, rescue and relief aid, video shooting, and map plotting and etc. In the control of the Unmanned Aerial Vehicle, the velocity detection and/or positioning control of the Unmanned Aerial Vehicle is a key technology. Currently, the velocity detection and/or the positioning control of the Unmanned Aerial Vehicle are mostly done via the positioning realized by the global positioning system (GPS). However, when the Unmanned Aerial Vehicle is located within a region where the GPS signal is relatively weak or a region without GPS signal coverage, the velocity detection and/or the positioning control of the Unmanned Aerial Vehicle are impossible. Moreover, currently the velocity detection and/or the positioning control of the Unmanned Aerial Vehicle are mostly performed by an algorithm based on a general scene. However, when the Unmanned Aerial Vehicle is actually located in a scene quite different from the general scene, the general scene-based-algorithm usually causes inaccurate positioning.